Evidence map›Paper›PMID 40140858›Full record

ArticleBMC health services research2025

The impact of the COVID-19 pandemic on governmental hospitals performance indicators in city of Yazd, Iran: an interrupted time-series analysis.

Mohammad Ranjbar, Mohammad Bazyar, Ommolbanin Sarkari, Hossein Ameri, Blake Angell, Yibeltal Assefa

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Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Mohammad RanjbarNational Center for Health Insurance Research, Tehran, Iran. ranjbar3079@gmail.com.
Mohammad BazyarDepartment of Health Management and Economics, Faculty of Health, Ilam University of Medical Sciences, Ilam, Iran.
Ommolbanin SarkariDepartment of Health Management and Economics, International Campus of Shahid Sadoughi University of Medical Sciences, Yazd, Iran. ihnd1234@gmail.com.
Hossein AmeriHealth Policy & Management Research Center, Department of Health Management and Economics, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Blake AngellCentre for Health Systems Science, the George Institute for Global Health, University of New South Wales, Sydney, Australia.
Yibeltal AssefaSchool of Public Health, The University of Queensland, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Covid-19 pandemic stretched health systems globally including in Iran. Hospital demand and performance was affected both directly and indirectly as a result of the pandemic. Analyzing hospital indicators can provide insights to deal with the consequences and challenges related to various aspects of future pandemics.

objectiveThis study aimed to investigate the impact of the Covid-19 pandemic on key performance indicators of public hospitals in Iran.

methodsIn this quasi-experimental study, we used time-series analysis to examine eight key indicators of hospital performance: number of outpatient visits, number of elective hospitalization, average length of stay, hospital mortality rate, number of surgeries, hospitalization rate, emergency visits, bed occupancy rate, and hospitals' revenue. Data were extracted from four public hospitals in Yazd at two time intervals, 15 months before and after the outbreak of COVID-19. Data were analysed using interrupted time series analysis models with STATA

resultsAverage length of stay (p = 0.02) and hospital mortality rate (p < 0.01) increased significantly following the outbreak of COVID-19, while the mean of other indicators such as number of outpatient visits (p < 0.01), number of elective hospitalization (p < 0.01), number of surgeries (p = 0.01), hospitalization rate (p < 0.01), emergency visits (p < 0.01) and bed occupancy rate (p < 0.01) decreased significantly. The Covid-19 pandemic had an immediately reverse significant impact on the level changes of "outpatient visits", "elective hospitalization", "hospitalization rate", "emergency visits" and "bed occupancy rate" indicators (p < 0.05). Although the trend of surgeries indicator was affected significantly (p = 0.01) after the covid-19 outbreak.

conclusionWe showed significant changes in most hospital indicators after the Covid-19 pandemic, reflecting the effect of this pandemic on the performance of hospitals. Understanding the impact of a pandemic on hospital indicators is necessary for decision-makers to effectively plan an effective pandemic response and to inform resource allocation decisions.

Indexed as

COVID-19Hospitals, PublicQuality Indicators, Health CareBed OccupancyElective Surgical ProceduresEmergency Service, HospitalHospitalizationHospital MortalityHumansInterrupted Time Series AnalysisIranLength of StayPandemicsSARS-CoV-2Covid-19Interrupted time series analysisPerformance indicatorsPublic hospital

Identifiers

PMID40140858
PMCPMC11948652

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.